{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6a3268e4",
   "metadata": {},
   "source": [
    "# OVHcloud\n",
    "\n",
    "> In order to use this model you need to create a new token on the AI Endpoints website: https://endpoints.ai.cloud.ovh.net/.\n",
    "\n",
    "This notebook explains how to use OVHCloudEmbeddings, which is included in the langchain_community package, to embed texts in langchain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3da0fce0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Embedding generated by OVHCloudEmbeddings: [0.013393167, 0.03732136, -0.0042296825, 0.042756177, 0.022484222, -0.0045062024, -0.039632313, -0.016722068, 0.035480227, 0.021987874, -0.007831321, -0.002374333, 0.14827625, 0.044154406, -0.038416132, -0.051982213, 0.0054677227, -0.030913774, 0.03872776, 0.00080121466, 0.06914864, -0.01889285, 0.051963896, -0.049868602, 0.032817934, -0.012699772, 0.029378777, -0.019135607, -0.014866451, 0.010978144, 0.036102116, -0.024129838, 0.0059551136, 0.025592148, 0.0330448, 0.05326782, -0.008618608, -0.04626763, 0.046697352, 0.007115799, 0.025649866, 0.02479821, -0.011125191, -0.011960746, 0.027974335, -0.008805084, -0.0014219242, -0.016421443, -0.042280562, -0.027239632, 0.013829875, 0.008757527, 0.024184346, 0.01559286, -0.05868668, -0.058345765, 0.048597623, 0.027461633, -0.03701432, 0.014960674, 0.0055076545, 0.011801827, 0.003185198, 0.024615683, 0.04377218, -0.02428408, -0.01129621, -0.008451086, -0.024531357, -0.029689042, 0.019617215, 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0.0074356734, -0.0019842882, -0.049663708, 0.035164695, -0.044908658, -0.05643445, 0.02870157, 0.03714114, 0.033664975, -0.013390485, -0.0004991374, 0.02155712, 0.021897627, 0.047690097, -0.01916393, -0.01362889, 0.025618015, 0.018122612, 0.036994122, -0.01447489, 0.040231027, -0.047183823, -0.020032013, 0.027981037]\n"
     ]
    }
   ],
   "source": [
    "from langchain_community.embeddings.ovhcloud import OVHCloudEmbeddings\n",
    "\n",
    "embedder = OVHCloudEmbeddings(\n",
    "    model_name=\"multilingual-e5-base\", region=\"kepler\", access_token=\"MyAccessToken\"\n",
    ")\n",
    "embed = embedder.embed_query(\"Hello World!\")\n",
    "\n",
    "\"\"\" verify \"\"\"\n",
    "print(f\"Embedding generated by OVHCloudEmbeddings: {embed}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47c9af05-4d25-40f2-9305-7bccf1e14c64",
   "metadata": {},
   "source": [
    "## Further reading\n",
    "- [Enhance your applications with AI Endpoints](https://blog.ovhcloud.com/enhance-your-applications-with-ai-endpoints/)\n",
    "- [How to use AI Endpoints and LangChain4j](https://blog.ovhcloud.com/how-to-use-ai-endpoints-and-langchain4j/)\n",
    "- [LLMs streaming with AI Endpoints and LangChain4j](https://blog.ovhcloud.com/llms-streaming-with-ai-endpoints-and-langchain4j/)\n",
    "- [How to use AI Endpoints and LangChain to create a chatbot](https://blog.ovhcloud.com/how-to-use-ai-endpoints-and-langchain-to-create-a-chatbot/)\n",
    "- [How to use AI Endpoints, LangChain and Javascript to create a chatbot](https://blog.ovhcloud.com/how-to-use-ai-endpoints-langchain-and-javascript-to-create-a-chatbot/)\n",
    "- [RAG chatbot using AI Endpoints and LangChain](https://blog.ovhcloud.com/rag-chatbot-using-ai-endpoints-and-langchain/)"
   ]
  }
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